Meta-analysis parameters computation: a Python approach to facilitate the crossing of experimental conditions
Methodology
2020-07-16 v1 Mathematical Software
Applications
Abstract
Meta-analysis is a data aggregation method that establishes an overall and objective level of evidence based on the results of several studies. It is necessary to maintain a high level of homogeneity in the aggregation of data collected from a systematic literature review. However, the current tools do not allow a cross-referencing of the experimental conditions that could explain the heterogeneity observed between studies. This article aims at proposing a Python programming code containing several functions allowing the analysis and rapid visualization of data from many studies, while allowing the possibility of cross-checking the results by experimental condition.
Cite
@article{arxiv.2007.07799,
title = {Meta-analysis parameters computation: a Python approach to facilitate the crossing of experimental conditions},
author = {Flavien Quijoux and Charles Truong and Aliénor Vienne-Jumeau and Laurent Oudre and François BERTIN-HUGAULT and Philippe ZAWIEJA and Marie LEFEVRE and Pierre-Paul VIDAL and Damien RICARD},
journal= {arXiv preprint arXiv:2007.07799},
year = {2020}
}